"Real-time NetEase web page scraping implementation" matching MCP servers:

Enables AI assistants to fetch public web pages as readable text or HTML, with caching, live refresh, and parallel job handling.

Thunderbit MCP lets AI agents search, scrape, and extract structured data from any website.

Enables German real-estate appraisal calculations, including property depreciation and purchase-price allocation, through MCP tools backed by AfaMax APIs.

Enables web research through multi-provider search, documentation lookup, public code search, and clean Markdown extraction from static or JavaScript-rendered pages via five read-only tools.

Ultra-lightweight headless browser for AI agents. Provides MCP tools for navigating URLs, extracting structured content, and building autonomous agent workflows.

Implementation of an MCP server for the RAG Web Browser Actor. This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.

Enables graph analysis over interconnected agent networks by computing centrality and authority scores, shortest paths, dependency orderings, maximum flows, and minimum spanning trees through MCP tools.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for QuickBooks Time (beta): https://www.cdata.com/download/download.aspx?sku=HCZK-V&type=beta

Enables secure validation of agent credentials through constant-time digest comparison, JWT HMAC-SHA256 checks, Merkle inclusion proofs, Schnorr zero-knowledge verification, and nonce replay protection. It integrates natively with MCP clients to harden autonomous agent authentication workflows.

Enables statistical forecasting and anomaly detection over numerical time-series data using Holt linear smoothing, multi-step projections, and variance-based confidence bands.

Enables coding agents to drive a real Playwright-backed browser session, navigating, observing, interacting, and capturing proof on web pages via MCP tools across stdio and Streamable HTTP transports.

A remote MCP server that lets AI agents share HTML pages with real people for visual review and collect their pinned notes as actionable feedback.

Enables autonomous agents to inspect live web pages, prune noisy DOM content down to semantic essentials, and bind each form field to agent state by matching input attributes, autocomplete hints, and regex validations. It also converts HTML/Markdown tables into type-inferred JSON records and scores agent action trajectories for precision, recall, and edit distance.

Enables autonomous web form inspection and schema auto-mapping by matching input attributes, autocomplete hints, and regex validations to agent state, while also pruning DOMs and converting tables into structured JSON for web agents.

Enables MCP-compatible agents to scrape web pages and distill them into clean Markdown by removing cookie banners, navbars, and ads for efficient consumption.

Enables agents to forecast numerical trends with zero-dependency Holt linear exponential smoothing, multi-step horizons, variance confidence bands, and supporting statistical anomaly detection, regression, hypothesis testing, and PCA.

A GitHub-based implementation of the Model Context Protocol that enables LLMs to access and manipulate data in a Universal Object Reference (UOR) framework, providing standardized interfaces for object management with decentralized storage.

Provides web access tools (fetch, search, sitemap crawl) through String AI's API, automatically handling anti-bot bypass, CAPTCHA, and JavaScript rendering.

Unleashes LLM-powered agents to autonomously execute and debug web apps directly in your code editor, with features like webapp navigation, network traffic capture, and console error collection.

Connects AI coding assistants to Snyk API & Web for onboarding scan targets, configuring authentication, running DAST scans, and triaging findings through natural language.